The present invention relates to image compression apparatus for compressing color imaging signals and image processing system for effecting compression, expansion and reproduction of color imaging signals, and more particularly relates to image compression apparatus and image processing system suitably used in those products such as a capsular endoscope or mobile phone in which power saving and size reduction are demanded more than image quality.
FIG. 1 is a block diagram showing an example of a general image processing system. In FIG. 1, numeral 101 denotes an imaging apparatus. The imaging apparatus 101 has a solid-state imaging device for receiving light from an object to output color imaging signals corresponding to the received light amount. The color imaging signals from the solid-state imaging device are transmitted as image data. To achieve an efficient transmission of image data, the image data are usually transmitted by way of processing at an image data compression apparatus 102. The image data compression apparatus 102 effects a compression processing based on the standard for example of JPEG (Joint Photographic Expert Group) or MPEG (Moving Picture Expert Group) for the inputted image data and subsequently transmits the compressed image data.
Supposing a single-chip sensor imaging device, in order to reduce degradation of image data due to the compression processing at the image data compression apparatus 102, a matrix operation is first effected to convert color imaging signals obtained by taking image in the prior-art imaging apparatus 101 into R (red), G (green), B (blue) signals, i.e., a total number of signals three times the total number of the color imaging signals. Subsequently, these color signals are subjected to a separate matrix operation to generate luminance signal Y and color difference signals Cr, Cb which are the signals to be inputted to the image data compression apparatus 102.
At an image data expansion apparatus 103 having received the transmitted, compressed image data, then, an expansion processing based on the standard is effected. Next, an image reproduction apparatus 104 converts Y, Cr, Cb signals obtained by the expansion processing into R, G, B signals by means of an inverse operation of the matrix operation to display an image thereof.
A more detailed explanation will be given below with respect to an image processing system which includes: the imaging apparatus 101 as described; image data compression apparatus 102 for compressing image data outputted from the imaging apparatus 101; image data expansion apparatus 103 for expanding the compressed image data outputted from the image data compression apparatus 102; and image reproduction apparatus 104.
As shown in FIG. 2, it includes a color filter 201-1, solid-state imaging device 201-2, simultaneous section 201-3, and luminance/color-difference signal converting section 201-4 as its front-end section 201. The color filter 201-1 is formed by arranging R, G, B color filter elements in a Bayer method for example as shown in FIG. 4A. The color filter 201-1 is then stuck onto the front side of the solid-state imaging device 201-2 so that light from an object enters the solid-state imaging device 201-2 through the color filter 201-1.
The solid-state imaging device 201-2 is for receiving the light from the object through the color filter 201-1 to output color imaging signals corresponding to the received light amount and is provided with a plurality of light receiving elements corresponding to each color filter element of the color filter 201-1. The output from the solid-state imaging device 201-2 is inputted to the simultaneous section 201-3 as color imaging signals. The simultaneous section 201-3 is a circuit for generating R, G, B signals based on the color imaging signals outputted from the solid-state imaging device 201-2, and the R, G, B signals are inputted to the luminance/color-difference conversion section 201-4. The luminance/color-difference conversion section 201-4 generates Y, Cr, Cb based on the R, G, B signals outputted from the simultaneous section 201-3.
The principle for generating Y, Cr, Cb signals is generally expressed by the equations of [Formula 1].Y=0.30×R+0.59×G+0.11×BGr=0.70×R+(−0.59)×G+(−0.11)×BGb=(−0.30)×R+(−0.59)×G+0.89×B  [Formula 1]
These Y, Cr, Cb signals are to be inputted as image data to an image compression means 202. As shown in FIG. 2, the image compression means 202 includes a frequency conversion section 202-1, quantizing section 202-2, and coding section 202-3. The frequency conversion section 202-1 is for computing spatial frequency components for Y, Cr, Cb signals within each block. In a standard of JPEG, for example, one block is constituted by eight signals horizontally and eight signals vertically, i.e., 8×8 signals for each block of Y, Cr, Cb, and these 8×8 signals are subjected to DCT (discrete cosine transformation), a type of orthogonal transformation, to be converted into spatial frequency components (DCT coefficient) Fmnij.
The transform equation of the DCT coefficients is generally expressed by [Formula 2]. (Provided that m, n in [Formula 2] indicate horizontal and vertical locations of DCT coefficient; and i, j indicate location of Y, Cr, Cb signals within the block. 0≦m,n,i,j≦7.)
                                          F            mnij                    =                                    1              4                        ⁢            CmCn            ⁢                                                  ⁢            cos            ⁢                                                            (                                                            2                      i                                        +                    1                                    )                                ⁢                m                ⁢                                                                  ⁢                π                            16                        ⁢            cos            ⁢                                                  ⁢                                                            (                                                            2                      ⁢                      j                                        +                    1                                    )                                ⁢                n                ⁢                                                                  ⁢                π                            16                                      ⁢                                  ⁢                  CmCn          =                      {                                                                                1                                          2                                                                                                            (                                                                  when                        ⁢                                                                                                  ⁢                        m                                            ,                                              n                        =                        0                                                              )                                                                                                1                                                                      (                                                                  when                        ⁢                                                                                                  ⁢                        m                                            ,                                              n                        ≠                        0                                                              )                                                                                                          [                  Formula          ⁢                                          ⁢          2                ]            
The spatial frequency components Fmnij are inputted to the quantizing section 202-2. The quantizing section 202-2 is for effecting quantization of the spatial frequency components Fmnij outputted from the frequency conversion section 202-1. The quantized spatial frequency components outputted from the quantizing section 202-2 are inputted to the coding section 202-3. The coding section 202-3 is for forming code data for the quantized spatial frequency components outputted from the quantizing section 202-2. In a standard of JPEG, for example, after a zigzag scanning, Huffman coding and run length coding are effected on the quantized spatial frequency components outputted from the quantizing section 202-2.
The code data are inputted to an expansion means 203. As shown in FIG. 2, the expansion means 203 includes a decoding section 203-1, inverse quantizing section 203-2, and inverse frequency conversion section 203-3. The expansion means 203 is for effecting an expansion processing corresponding to the compression effected at the image compression means 202 and outputs Y, Cr, Cb signals. In a standard of JPEG, for example, a run-length decoding, Huffman decoding, inverse quantization, and inverse DCT are effected.
The Y, Cr, Cb signals outputted from the expansion means 203 are inputted to a back-end section 204. As shown in FIG. 2, the back-end section 204 includes a color signal converting section 204-1. The color signal converting section is for generating R, G, B signals based on the Y, Cr, Cb signals outputted from the expansion means 203. It should be noted that the principle for generating R, G, B signals is an inverse operation of the principle for generating Y, Cr, Cb signals as shown in [Formula 1].